Robust Structure-activity Relationship Research Articles

Descriptive molecular pharmacology of the δ opioid receptor (DOR): A computational study with structural approach.

This work focuses on the δ receptor (DOR), a G protein-coupled receptor (GPCR) belonging to the opioid receptor group. DOR is expressed in numerous tissues, particularly within the nervous system. Our study explores computationally the receptor's interactions with various ligands, including opiates and opioid peptides. It elucidates how these interactions influence the δ receptor response, relevant in a wide range of health and pathological processes. Thus, our investigation aims to explore the significance of DOR as an incoming drug target for pain relief and neurodegenerative diseases and as a source for novel opioid non-narcotic analgesic alternatives. We analyze the receptor's structural properties and interactions using Molecular Dynamics (MD) simulations and Gaussian-accelerated MD across different functional states. To thoroughly assess the primary differences in the structural and conformational ensembles across our different simulated systems, we initiated our study with 1 μs of conventional Molecular Dynamics. The strategy was chosen to encompass the full activation cycle of GPCRs, as activation processes typically occur within this microsecond range. Following the cMD, we extended our study with an additional 100 ns of Gaussian accelerated Molecular Dynamics (GaMD) to enhance the sampling of conformational states. This simulation approach allowed us to capture a comprehensive range of dynamic interactions and conformational changes that are crucial for GPCR activation as influenced by different ligands. Our study includes comparing agonist and antagonist complexes to uncover the collective patterns of their functional states, regarding activation, blocking, and inactivation of DOR, starting from experimental data. In addition, we also explored interactions between agonist and antagonist molecules from opiate and opioid classifications to establish robust structure-activity relationships. These interactions have been systematically quantified using a Quantitative Structure-Activity Relationships (QSAR) model. This research significantly contributes to our understanding of this significant pharmacological target, which is emerging as an attractive subject for drug development.

Robust Strategy for Hit-to-Lead Discovery: NMR for SAR.

Establishing robust structure-activity relationships (SARs) is key to successful drug discovery campaigns, yet it often remains elusive due to screening and hit validation artifacts (false positives and false negatives), which frequently result in unproductive downstream expenditures of time and resources. To address this issue, we developed an integrative biophysics-driven strategy that expedites hit-to-lead discovery, mitigates false positives/negatives and common hit validation errors, and provides a robust approach to obtaining accurate binding and affinity measurements. The advantage of this method is that it vastly improves the clarity and reproducibility for affinity-driven SAR by monitoring and eliminating confounding factors. We demonstrate the ease at which high-quality micromolar binders can be generated from the initial millimolar fragment screening hits against an "undruggable" protein target, HRas.

Precision Design of Antimicrobial Surfaces.

The overall expectation from an antimicrobial surface has been high considering the need for efficiency in preventing the attachment and growth of pathogenic microbes, durability, safety to both humans and environment as well as cost-effectiveness. To date, antimicrobial surface design has been mostly conducted liberally, without rigorous consideration of establishing robust structure-activity relationships for each design strategy or of the use intended for a specific antimicrobial material. However, the variability among the domain bacteria, which is the most diverse of all, alongside the highly dynamic nature of the bacteria-surface interface have taught us that the likelihood of finding universal antimicrobial surfaces is low. In this perspective we discuss some of the current hurdles faced by research in this promising field, emphasizing the relevance and complexity of probing the bacteria-surface interface, and explain why we feel it would greatly benefit from a more streamlined ad-hoc approach.

High-throughput virtual screening of novel dihydropyrimidine monastrol analogs reveals robust structure-activity relationship to kinesin Eg5 binding thermodynamics

As cancer continues to take millions of lives worldwide, the need to create effective therapeutics for the disease persists. The kinesin Eg5 assembly motor protein is a promising target for cancer therapeutics as inhibition of this protein leads to cell cycle arrest. Monastrol, a small dihydropyrimidine-based molecule capable of inhibiting the kinesin Eg5 function, has attracted the attention of medicinal chemists with its potency, affinity, and specificity to the highly targeted loop5/α2/α3 allosteric binding pocket. In this work, we employed high-throughput virtual screening (HTVS) to identify potential small molecule Eg5 inhibitors from a designed set of novel dihydropyrimidine analogs structurally similar to monastrol. Density functional theory (DFT) calculations and protein-ligand docking experiments revealed that the analogs with geranyl ester substitutions exhibited the greatest binding affinities to the allosteric binding pocket of kinesin Eg5. In-depth analysis of the binding pocket amino acid residues and calculations of the cLogP value for each compound demonstrated qualitatively and quantitatively that strong hydrophobic interactions of the ester functionality with kinesin Eg5 are of great significance in the improved binding of dihydropyrimidine analogs. This establishment of a quantitative structure-activity relationship to kinesin Eg5 binding thermodynamics using HTVS revealed the discovery of improved dihydropyrimidine-based inhibitors capable of advancing society’s progress in the fight against cancer.

Structure-Based and Molecular Modeling Studies for the Discovery of Cyclic Imides as Reversible Cruzain Inhibitors With Potent Anti-Trypanosoma cruzi Activity.

Chagas disease causes ~10,000 deaths each year, mainly in Latin America, where it is endemic. The currently available chemotherapeutic agents are ineffective in the chronic stage of the disease, and the lack of pharmaceutical innovation for Chagas disease highlights the urgent need for the development of new drugs. The enzyme cruzain, the main cysteine protease of Trypanosoma cruzi, has been explored as a validated molecular target for drug discovery. Herein, the design, molecular modeling studies, synthesis, and biological evaluation of cyclic imides as cruzain inhibitors are described. Starting with a micromolar-range cruzain inhibitor (3a, IC50 = 2.2 μM), this molecular optimization strategy resulted in the nanomolar-range inhibitor 10j (IC50 = 0.6 μM), which is highly active against T. cruzi intracellular amastigotes (IC50 = 1.0 μM). Moreover, most compounds were selective toward T. cruzi over human fibroblasts, which were used as host cells, and are less toxic to hepatic cells than the marketed drug benznidazole. This study enabled the discovery of novel chemical diversity and established robust structure-activity relationships to guide the design of optimized cruzain inhibitors as new trypanocidal agents.

4-(3-Nitrophenyl)thiazol-2-ylhydrazone derivatives as antioxidants and selective hMAO-B inhibitors: synthesis, biological activity and computational analysis

A new series of 4-(3-nitrophenyl)thiazol-2-ylhydrazone derivatives were designed, synthesised, and evaluated to assess their inhibitory effect on the human monoamine oxidase (hMAO) A and B isoforms. Different (un)substituted (hetero)aromatic substituents were linked to N1 of the hydrazone in order to establish robust structure–activity relationships. The results of the biological testing demonstrated that the presence of the hydrazothiazole nucleus bearing at C4 a phenyl ring functionalised at the meta position with a nitro group represents an important pharmacophoric feature to obtain selective and reversible human MAO-B inhibition for the treatment of neurodegenerative disorders. In addition, the most potent and selective MAO-B inhibitors were evaluated in silico as potential cholinesterase (AChE/BuChE) inhibitors and in vitro for antioxidant activities. The results obtained from molecular modelling studies provided insight into the multiple interactions and structural requirements for the reported MAO inhibitory properties.

Design, synthesis and biological activity of selective hCAs inhibitors based on 2-(benzylsulfinyl)benzoic acid scaffold

A large library of derivatives based on the scaffold of 2-(benzylsulfinyl)benzoic acid were synthesised and tested as atypical inhibitors against four different isoforms of human carbonic anhydrase (hCA I, II, IX and XII, EC 4.2.1.1). The exploration of the chemical space around the main functional groups led to the discovery of selective hCA IX inhibitors in the micromolar/nanomolar range, thus establishing robust structure-activity relationships within this versatile scaffold. HPLC separation of some selected chiral compounds and biological evaluation of the corresponding enantiomers was performed along with molecular modelling studies on the most active derivatives.

Identification of Allosteric Modulators of Metabotropic Glutamate 7 Receptor Using Proteochemometric Modeling.

Proteochemometric modeling (PCM) is a computational approach that can be considered an extension of quantitative structure–activity relationship (QSAR) modeling, where a single model incorporates information for a family of targets and all the associated ligands instead of modeling activity versus one target. This is especially useful for situations where bioactivity data exists for similar proteins but is scarce for the protein of interest. Here we demonstrate the application of PCM to identify allosteric modulators of metabotropic glutamate (mGlu) receptors. Given our long-running interest in modulating mGlu receptor function we compiled a matrix of compound-target bioactivity data. Some members of the mGlu family are well explored both internally and in the public domain, while there are much fewer examples of ligands for other targets such as the mGlu7 receptor. Using a PCM approach mGlu7 receptor hits were found. In comparison to conventional single target modeling the identified hits were more diverse, had a better confirmation rate, and provide starting points for further exploration. We conclude that the robust structure–activity relationship from well explored target family members translated to better quality hits for PCM compared to virtual screening (VS) based on a single target.

Discovery of Imidazo[1,2-a]pyridine Ethers and Squaramides as Selective and Potent Inhibitors of Mycobacterial Adenosine Triphosphate (ATP) Synthesis.

The approval of bedaquiline to treat tuberculosis has validated adenosine triphosphate (ATP) synthase as an attractive target to kill Mycobacterium tuberculosis (Mtb). Herein, we report the discovery of two diverse lead series imidazo[1,2-a]pyridine ethers (IPE) and squaramides (SQA) as inhibitors of mycobacterial ATP synthesis. Through medicinal chemistry exploration, we established a robust structure-activity relationship of these two scaffolds, resulting in nanomolar potencies in an ATP synthesis inhibition assay. A biochemical deconvolution cascade suggested cytochrome c oxidase as the potential target of IPE class of molecules, whereas characterization of spontaneous resistant mutants of SQAs unambiguously identified ATP synthase as its molecular target. Absence of cross resistance against bedaquiline resistant mutants suggested a different binding site for SQAs on ATP synthase. Furthermore, SQAs were found to be noncytotoxic and demonstrated efficacy in a mouse model of tuberculosis infection.

A Database of the Structural and Electronic Properties of Prussian Blue, Prussian White, and Berlin Green Compounds through Density Functional Theory.

Prussian blue and its related compounds are formed by cheap and abundant metals and have shown their importance in the generation of new fuels by renewable sources. To optimize these compounds it is important to understand their electronic structure and thus establish robust structure-activity relationships. To this end, we employed theoretical simulations based on density functional theory, employing functionals of different degree of complexity, including pure generalized gradient approximation (GGA) and GGA+U functionals, which introduce self-interaction correction terms through the Hubbard parameter, and compared those to the hybrid functionals HSE03 and HSE06. With this robust setup, we can identify an appropriate computational scheme that provides the best compromise between computational demand and accuracy. A complete database considering Berlin green and Prussian blue and white for all alkaline cations is presented.

Left-Hand Side Exploration of Novel Bacterial Topoisomerase Inhibitors to Improve Selectivity against hERG Binding

Structure-activity relationship (SAR) exploration on the left-hand side (LHS) of a novel class of bacterial topoisomerase inhibitors led to a significant improvement in the selectivity against hERG cardiac channel binding with concomitant potent antimycobacterial activity. Bulky polar substituents at the C-7 position of the naphthyridone ring did not disturb its positioning between two base pairs of DNA. Further optimization of the polar substituents on the LHS of the naphthyridone ring led to potent antimycobacterial activity (Mtb MIC = 0.06 μM) against Mycobacterium tuberculosis (Mtb). Additionally, this knowledge provided a robust SAR understanding to mitigate the hERG risk. This compound class inhibits Mtb DNA gyrase and retains its antimycobacterial activity against moxifloxacin-resistant strains of Mtb. Finally, we demonstrate in vivo proof of concept in an acute mouse model of TB following oral administration of compound 19.

Profiling a structure activity relationship library for immunological activity in human PBMCs: multiplexed measurements of cell phenotype, viability, and cytokine secretion from a single high throughput screen (TECH2P.923)

Abstract The success of immunomodulatory approaches for the treatment of disease has generated tremendous interest in discovery of new immunotherapy based therapeutics. Immunotherapy has the potential of affecting - positively and negatively - the myriad interactions among cells and signaling molecules regulating the immune system, and projects should include high throughput screening campaigns aimed at profiling the effects of compounds on these complex interactions. We describe a no-wash, high throughput screen that provides a multiparameter activity profile for a structure activity relationship (SAR) library of immunomodulatory compounds. Seven known immunomodulatory compounds were used as templates to generate an SAR expansion library of 1438 compounds. The selection utilized a combination of various substructure and similarity search methods combined with the generation of virtual templates. Phytohemagglutinin (PHA) activated PBMCs were treated with the compounds at two doses, 10µM and 50µM. Immunophenotyping was done by α-CD3 and α-CD8 antibodies and differential toxic effects of compounds on the viability of individual cell subsets plus effects on the secretion of three cytokines were used to generate an immunological profile for each compound tested. We demonstrate the combination of a robust SAR expansion system with high throughput, multiplex screening on primary cells to generate activity profiles that can be used for identifying viable therapeutic candidates.

Designing innovative therapies for neuropathic pain: pros and cons of target-based drug discovery.

Designing innovative therapies for neuropathic pain: pros and cons of target-based drug discovery.

Aminopyrazinamides: Novel and Specific GyrB Inhibitors that Kill Replicating and Nonreplicating Mycobacterium tuberculosis

Aminopyrazinamides originated from a high throughput screen targeting the Mycobacterium smegmatis (Msm) GyrB ATPase. This series displays chemical tractability, robust structure-activity relationship, and potent antitubercular activity. The crystal structure of Msm GyrB in complex with one of the aminopyrazinamides revealed promising attributes of specificity against other broad spectrum pathogens and selectivity against eukaryotic kinases due to novel interactions at hydrophobic pocket, unlike other known GyrB inhibitors. The aminopyrazinamides display excellent mycobacterial kill under in vitro, intracellular, and hypoxic conditions.

Outlier Mining in High Throughput Screening Experiments

A data mining procedure for the rapid scoring of high-throughput screening (HTS) compounds is presented. The method is particularly useful for monitoring the quality of HTS data and tracking outliers in automated pharmaceutical or agrochemical screening, thus providing more complete and thorough structure-activity relationship (SAR) information. The method is based on the utilization of the assumed relationship between the structure of the screened compounds and the biological activity on a given screen expressed on a binary scale. By means of a data mining method, a SAR description of the data is developed that assigns probabilities of being a hit to each compound of the screen. Then, an inconsistency score expressing the degree of deviation between the adequacy of the SAR description and the actual biological activity is computed. The inconsistency score enables the identification of potential outliers that can be primed for validation experiments. The approach is particularly useful for detecting false-negative outliers and for identifying SAR-compliant hit/nonhit borderline compounds, both of which are classes of compounds that can contribute substantially to the development and understanding of robust SARs. In a first implementation of the method, one- and two-dimensional descriptors are used for encoding molecular structure information and logistic regression for calculating hits/nonhits probability scores. The approach was validated on three data sets, the first one from a publicly available screening data set and the second and third from in-house HTS screening campaigns. Because of its simplicity, robustness, and accuracy, the procedure is suitable for automation.

A robust structure-activity relationship (SAR) model for esters that cause skin irritation in humans.

A structure-activity relationship (SAR) model has been developed to discriminate skin irritant from nonirritant esters. The model is based on the physicochemical properties of 42 esters that were tested in humans for skin irritation. Nineteen physicochemical parameters that represent transport, electronic, and steric properties were calculated for each chemical. Best subsets regression analysis indicated candidate models for further analysis. Regression analyses identified significant models (p < 0.05) that had variables that were also significant (p < 0.05). These candidate models were evaluated using linear discriminant analysis to determine if the irritant esters could be discriminated from nonirritant esters. The stability of the model was evident from the consistency of parameters among ten submodels generated using multiple random sampling of the database. The sensitivity of the ten models, evaluated by "leave-one-out" cross-validation, ranged from 0. 846 to 0.923, with a mean of 0.885 +/- 0.025 (95% CI). The specificity ranged from 0.615 to 0.923, with a mean of 0.738 +/- 0.06 (CI). Compared with nonirritant esters, irritant esters had lower density, lower water solubility, lower sum of partial positive charges, higher Hansen hydrogen bonding parameter, and higher Hansen dispersion parameter. The results indicate that physicochemical features of esters contribute to their ability to cause skin irritation in humans, and that chemical partitioning into the epidermis and intermolecular reactions are likely important components of the response. This model is applicable for prediction of human irritation of esters yet untested.